Approaches to Measure Efficiency in Primary Care: A Systematic Literature Review

A Multi-dimensional Framework of Valued Output for Primary Care in England

Improving efficiency and productivity are key aspects to ensure that general practices in England can meet the needs of a growing population with increasingly demanding and costly healthcare needs. However, current evidence on the efficiency and productivity of general practices is weak, partly due to suboptimal approaches to measure their 'valued' output. To overcome this limitation, this paper presents a multi-dimensional framework and indicators of valued output from the healthcare decision-maker's perspective. We identified existing primary care performance frameworks through a targeted literature review. We reviewed the frameworks and selected the dimensions relating to the impact on patients' health outcomes, corresponding with the definition of 'valued' output from the healthcare decision-maker perspective. For each dimension, we reviewed the National Institute for Health and Care Excellence (NICE) evidence base and guidance on best practice to develop indicators of valued output. Clinical experts and representatives of the main primary care stakeholders reviewed and validated the framework's comprehensiveness and development process. Based on a review of three existing frameworks, we synthesised a multi-dimensional output framework comprising 13 dimensions for significant primary care-related conditions and services and 51 indicators of valued output. Each indicator of valued output measures a healthcare episode and the resulting impact on patient's health. The multi-dimensional framework and indicators provide a theoretical tool to improve the measurement of primary care output in economic efficiency and productivity studies. Future research should explore the measurability of the indicators through available datasets and the implementation of the framework through analytical approaches for efficiency measurement.

The hidden work of general practitioners: An ethnography

High quality primary care is a foundational element of effective health services. Internationally, primary care physicians (general practitioners (GPs), family doctors) are experiencing significant workload pressures. How non-patient-facing work contributes to these pressures and what constitutes this work is poorly understood and often unrecognised and undervalued by patients, policy makers, and even clinicians engaged in it. This paper examines non-patient-facing work ethnographically, informed by practice theory, the Listening Guide, and empirical ethics. Ethnographic observations (104 h), in-depth interviews (n = 16; 8 with GPs and 8 with other primary care staff) and reflexive workshops were conducted in two general practices in England. Our analysis shows that 'hidden work' was integral to direct patient care, involving diverse clinical practices such as: interpreting test results; crafting referrals; and accepting interruptions from clinical colleagues. We suggest the term 'hidden care work' more accurately reflects the care-ful nature of this work, which was laden with ambiguity and clinical uncertainty. Completing hidden care work outside of expected working hours was normalised, creating feelings of inefficiency, and exacerbating workload pressure. Pushing tasks forward into an imagined future (when conditions might allow its completion) commonly led to overspill into GPs' own time. GPs experienced tension between their desire to provide safe, continuous, 'caring' care and the desire to work a manageable day, in a context of increasing demand and burgeoning complexity.

Precision Medicine-Are We There Yet? A Narrative Review of Precision Medicine's Applicability in Primary Care

Precision medicine (PM), also termed stratified, individualised, targeted, or personalised medicine, embraces a rapidly expanding area of research, knowledge, and practice. It brings together two emerging health technologies to deliver better individualised care: the many "-omics" arising from increased capacity to understand the human genome and "big data" and data analytics, including artificial intelligence (AI). PM has the potential to transform an individual's health, moving from population-based disease prevention to more personalised management. There is however a tension between the two, with a real risk that this will exacerbate health inequalities and divert funds and attention from basic healthcare requirements leading to worse health outcomes for many. All areas of medicine should consider how this will affect their practice, with PM now strongly encouraged and supported by government initiatives and research funding. In this review, we discuss examples of PM in current practice and its emerging applications in primary care, such as clinical prediction tools that incorporate genomic markers and pharmacogenomic testing. We look towards potential future applications and consider some key questions for PM, including evidence of its real-world impact, its affordability, the risk of exacerbating health inequalities, and the computational and storage challenges of applying PM technologies at scale.

The effect of general practice team composition and climate on staff and patient experiences: a systematic review

BACKGROUND

Recent policy initiatives seeking to address the workforce crisis in general practice have promoted greater multidisciplinarity. Evidence is lacking on how changes in staffing and the relational climate in practice teams affect the experiences of staff and patients.

AIM

To synthesise evidence on how the composition of the practice workforce and team climate affect staff job satisfaction and burnout, and the processes and quality of care for patients.

DESIGN & SETTING

A systematic literature review of international evidence.

METHOD

Four different searches were carried out using MEDLINE, Embase, Cochrane Library, CINAHL, PsycINFO, and Web of Science. Evidence from English language articles from 2012-2022 was identified, with no restriction on study design. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed and data were synthesised thematically.

RESULTS

In total, 11 studies in primary healthcare settings were included, 10 from US integrated healthcare systems, one from Canada. Findings indicated that when teams are understaffed and work environments are stressful, patient care and staff wellbeing suffer. However, a good relational climate can buffer against burnout and protect patient care quality in situations of high workload. Good team dynamics and stable team membership are important for patient care coordination and job satisfaction. Female physicians are at greater risk of burnout.

CONCLUSION

Evidence regarding team composition and team climate in relation to staff and patient outcomes in general practice remains limited. Challenges exist when drawing conclusions across different team compositions and definitions of team climate. Further research is needed to explore the conditions that generate a 'good' climate.

Exploring the association between primary care efficiency and health system characteristics across European countries: a two-stage data envelopment analysis

BACKGROUND

Primary care is widely seen as a core component of resilient and sustainable health systems, yet its efficiency is not well understood and there is a lack of evidence about how primary care efficiency is associated with health system characteristics. We examine this issue through the lens of diabetes care, which has a well-established evidence base for effective treatment and has previously been used as a tracer condition to measure health system performance.

METHODS

We developed a conceptual framework to guide the analysis of primary care efficiency. Using data on 18 European countries during 2010-2016 from several international databases, we applied a two-stage data envelopment analysis to estimate (i) technical efficiency of primary care and (ii) the association between efficiency and health system characteristics.

RESULTS

Countries varied widely in terms of primary care efficiency, with efficiency scores depending on the range of population characteristics adjusted for. Higher efficiency was associated with bonus payments for the prevention and management of chronic conditions, nurse-led follow-up, and a financial incentive or requirement for patients to obtain a referral to specialist care. Conversely, lower efficiency was associated with higher rates of curative care beds and financial incentives for patients to register with a primary care provider.

CONCLUSIONS

Our results underline the importance of considering differences in population characteristics when comparing country performance on primary care efficiency. We highlight several policies that could enhance the efficiency of primary care. Improvements in data collection would enable more comprehensive assessments of primary care efficiency across countries, which in turn could more effectively inform policymaking.

Estimating productivity levels in primary medical services across clinical commissioning groups in England and the impact of the COVID-19 pandemic: a data envelopment analysis

OBJECTIVES

To assess the relative productivity of primary medical services in England and the impact of the COVID-19 pandemic on productivity levels.

SETTING

Primary medical services for 59 million patients (98% of the population in England), in 101 clinical commissioning groups (CCGs), across two time periods: period 1, pre-pandemic, April to December 2019 and period 2, pandemic, April to December 2020.

METHODS

We use data envelopment analysis (DEA) to assess relative productivity with four input measures (the number of full-time equivalent general practitioners, nurses, other direct patient contact staff and administrators), and five output measures (face-to-face appointments, remote consultations, home visits, referrals to secondary care and prescriptions). Our units of analysis were CCGs. DEA assigns an efficiency score to a CCG, taking a value between 0 and 100%, by benchmarking it against the most productive CCGs. We use Tobit regression to examine the association between productivity and other factors.

RESULTS

The mean bias-corrected efficiency score of primary medical services in CCGs was 92.9% (interquartile range 92.0% to 95.7%) in period 1, falling to 90.6% (interquartile range 86.8% to 95.2%) in period 2. In period 1, CCGs with a higher proportion of registered patients aged over 65 years, higher levels of deprivation, lower levels of disease prevalence, higher nurse to GP ratios and higher GP to other direct patient contact staff ratios, achieved statistically significantly higher general practice efficiency scores (p < 0.05). In period 2, only the ratio of GP to other direct patient contact staff was associated with efficiency scores (p > 0.05).

CONCLUSIONS

Our analysis indicates only modest geographic variation in productivity of primary medical services when measured at the level of clinical commissioning groups and a small reduction in productivity during the pandemic. Further work to establish relative productivity of individual GP practices is warranted once sufficient data on appointment rates by GP practice is available.

The Balanced Allocation of Medical and Health Resources in Urban Areas of China from the Perspective of Sustainable Development: A Case Study of Nanjing

The balanced allocation of medical and health resources is an important basis for the sustainable development of health undertakings. In recent years, China has made remarkable achievements in the medical and health services, but there is still a phenomenon of unbalanced allocation of medical and health resources among different regions, which has become an urgent problem to be solved in deepening the reform of the medical and health system during the 14th Five-Year Plan period. From the perspective of people’s needs for health, this study analyzed the equity and efficiency of urban medical and health resources allocation in China by using the Theil index method and DEA method. Meanwhile, the authors used the coupling coordination degree model to construct a balanced development model with equity and efficiency as subsystems, taking the city of Nanjing as an example to analyze its balanced allocation of medical and health resources from 2008 to 2019. In general, taking Nanjing as an example, it shows that the balanced allocation of medical and health resources in Chinese cities is good, but in geographical dimension, the level of balanced allocation is low, and there are still significant differences in the equity and efficiency of allocation among regions. In the future, the government can strengthen the rationality of regional planning, appropriately increasing health investment and medical supply, considering both equity and efficiency to further realize the balanced allocation of medical and health resources and improve the sustainability of urban medical service system. The main contribution of this paper lies in that, from the perspective of sustainable development, the evaluation system is integrated to measure the equity and efficiency respectively, and the balanced development model is used to investigate the allocation of urban medical and health resources. The research results can provide reference for optimizing resources allocation and promoting the sustainable development of medical and health undertakings.